The present disclosure generally relates to image processing and, in particular, to semantically segmenting an image.
Semantically segmenting (e.g., labeling) an image is useful in many image processing applications. For example, after portions of an image are labeled, the labeled portions of the image may be quickly identified and/or processed in different ways depending on the label. Certain types of image processing may remove image elements with a particular label in order to simplify the image. Facial recognition applications may focus specific facial recognition techniques on image elements with certain labels (e.g., a “face” label or a “person” label) in order to increase performance and accuracy of the facial recognition processes.
Image labeling may also be helpful in certain applications where images taken in the public are published and, in order to protect the privacy of individuals, portions of the image showing a person's face or a motor vehicle's license plate may be blurred before the images are published. For example, a blurring application may conserve computing resources and time as well as increase accuracy by focusing certain blurring processes on portions of an image labeled “car,” “license plate,” “person,” or “face.”
Methods for labeling an image typically analyze photographic data (e.g., the color histogram, the texture histogram, etc.) of an image in order to segment the image.